Salim T. S. Al-Hassani from the University of Manchester presented at KAUST's 2019 Winter Enrichment Program about the contributions of Muslim civilization to science and engineering. The lecture highlighted inventions like early clocks from Muslim heritage, including Al-Jazari's elephant clock. Al-Hassani aims to address the neglect of non-European cultures' impact on humanity. Why it matters: The talk emphasizes the historical significance of Islamic contributions to science and technology, relevant for promoting STEM education and cultural awareness in the region.
Historian Mike Bruton spoke at KAUST about scientific disruptors from the House of Wisdom during the Islamic Golden Age. These scholars made contributions like introducing the concept of zero and debunking the Greek theory of sight. Ibn al-Haytham revolutionized knowledge of optics, demonstrating that light bounces off objects and enters our eyes. Why it matters: The lecture highlights the significant scientific advancements made during the Islamic Golden Age and their lasting impact on modern civilization.
This paper proposes a smart dome model for mosques that uses AI to control dome movements based on weather conditions and overcrowding. The model utilizes Congested Scene Recognition Network (CSRNet) and fuzzy logic techniques in Python to determine when to open and close the domes to maintain fresh air and sunlight. The goal is to automatically manage dome operation based on real-time data, specifying the duration for which the domes should remain open each hour.
A proposed recognition system aims to identify missing persons, deceased individuals, and lost objects during the Hajj and Umrah pilgrimages in Saudi Arabia. The system intends to leverage facial recognition and object identification to manage the large crowds expected in the coming decade, estimated to reach 20 million pilgrims. It will be integrated into the CrowdSensing system for crowd estimation, management, and safety.
MASARAT SA has developed Mubeen, a proprietary Arabic language model specializing in Arabic linguistics, Islamic studies, and cultural heritage. Mubeen was trained using native Arabic sources, including digitized historical manuscripts processed via a proprietary Arabic OCR engine. The model employs a Practical Closure Architecture to improve user intent understanding and provide decisive guidance. Why it matters: Mubeen addresses the utility gap in current Arabic LLMs by focusing on native Arabic data and cultural authenticity, which is critical for heritage preservation and alignment with Saudi Vision 2030.
Researchers introduce TimeTravel, a benchmark dataset for evaluating large multimodal models (LMMs) on historical and cultural artifacts. The benchmark comprises 10,250 expert-verified samples across 266 cultures and 10 historical regions, designed to assess AI in tasks like classification and interpretation of manuscripts, artworks, inscriptions, and archaeological discoveries. The goal is to establish AI as a reliable partner in preserving cultural heritage and assisting researchers.
This paper proposes a smart dome system for mosques that uses machine learning to automatically control dome ventilation based on weather conditions and outside temperatures. The system was tested on the Prophet Mosque in Saudi Arabia using K-Nearest Neighbors and Decision Tree algorithms. The Decision Tree algorithm achieved a higher accuracy of 98% compared to 95% for the k-NN algorithm.